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This is the repository for my R project on modeling historical weather data in Santa Barbara.

HTML 99.94% R 0.06%
machine-learning r boosted-decision-trees boosted-trees data-science decision-trees linear-regression random-forest regression-trees rmarkdown

sb-weather-regression's Introduction

PSTAT131Final

This is a project I completed for my PSTAT 131 - Introduction to Statistical Machine Learning class at UCSB.

The "PSTAT131Final.Rproj" file contains this project.

The full project report is available at "PSTAT-131-Final-Project.html".

You can view the R Markdown file that was knitted into the completed HTML file at "PSTAT 131 Final Project.Rmd".

The "weather_codebook.txt" file contains information on each of the columns in my dataset.

The ".RData" files are saved versions of each of my models: a regression decision tree, a random forest with bootstrap aggregation, a boosted trees model, and a linear regression model.

"DecisionTree.txt" contains a Google Drive link to the full visualization of my regression decision tree model. Since the image was 1.09 GB in size, I could not include it in the final project. As such, I included a screenshot instead.

"weatherdatanew.csv" is my raw data file. Data was collected from Weather Underground and cleaned manually.

"eda.R" is my Exploratory Data Analysis file.

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